CN107703544B - Change oil gas forecasting method with offset distance based on the indication using prestack seismic amplitude of geostatistics - Google Patents
Change oil gas forecasting method with offset distance based on the indication using prestack seismic amplitude of geostatistics Download PDFInfo
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- CN107703544B CN107703544B CN201710885605.7A CN201710885605A CN107703544B CN 107703544 B CN107703544 B CN 107703544B CN 201710885605 A CN201710885605 A CN 201710885605A CN 107703544 B CN107703544 B CN 107703544B
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- 238000013277 forecasting method Methods 0.000 title claims abstract description 14
- 238000004458 analytical method Methods 0.000 claims abstract description 27
- 238000000034 method Methods 0.000 claims abstract description 14
- 239000003209 petroleum derivative Substances 0.000 claims abstract description 6
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 claims description 7
- 239000010931 gold Substances 0.000 claims description 7
- 229910052737 gold Inorganic materials 0.000 claims description 7
- 238000004422 calculation algorithm Methods 0.000 claims description 6
- 238000005295 random walk Methods 0.000 claims description 6
- 230000005012 migration Effects 0.000 claims description 4
- 238000013508 migration Methods 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 239000012530 fluid Substances 0.000 abstract description 9
- 238000004088 simulation Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 3
- 239000011435 rock Substances 0.000 description 2
- 239000004215 Carbon black (E152) Substances 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 229930195733 hydrocarbon Natural products 0.000 description 1
- 150000002430 hydrocarbons Chemical class 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000011148 porous material Substances 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/30—Analysis
- G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/50—Corrections or adjustments related to wave propagation
- G01V2210/51—Migration
- G01V2210/512—Pre-stack
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/61—Analysis by combining or comparing a seismic data set with other data
- G01V2210/616—Data from specific type of measurement
- G01V2210/6169—Data from specific type of measurement using well-logging
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/66—Subsurface modeling
- G01V2210/665—Subsurface modeling using geostatistical modeling
- G01V2210/6652—Kriging
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- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Acoustics & Sound (AREA)
- Environmental & Geological Engineering (AREA)
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- General Life Sciences & Earth Sciences (AREA)
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Abstract
Oil gas forecasting method is changed with offset distance based on the indication using prestack seismic amplitude of geostatistical analysis the present invention provides a kind of.The oil gas forecasting method includes: to establish oil and gas indication curve according to log data, and on oil and gas indication curve, oil gas section has the first oil and gas indication value, and non-oil gas section has the second oil and gas indication value；AVO attribute volume is calculated；Analysis obtains the oil and gas indication curve optimal AVO attribute volume best with well bypass road AVO attribute data correlation；Oil gas section part non-in oil and gas indication curve and oil gas section part are subjected to histogram analysis with optimal AVO attribute volume respectively, the subordinating degree function relationship of non-oil gas section part and oil gas section part in oil and gas indication curve is calculated；Geostatistical analysis is carried out to oil and gas indication curve and obtains variogram；Oil gas sunykatuib analysis, which is carried out, using subordinating degree function relationship and variogram obtains petroleum-gas prediction result.It can be improved the precision and resolution ratio of fluid prediction according to the method for the present invention.
Description
Technical field
The invention belongs to the fluid prediction methods in geophysical exploration technology, and more particularly, being related to one kind can be high
Predict to precision, high-resolution the geostatistics AVO analysis method of thin reservoir fluid.
Background technique
AVO (Amplitude variation offset, amplitude variation with Offset) technology is that a kind of research earthquake is anti-
Penetrate the technology that amplitude changes with geophone offset, amplitude is the letter of subsurface rock and pore-fluid elastic parameter with the variation of offset distance
Number, therefore the subsurface lithologic and its property of pore fluid reflected according to AVO changing rule can be used to directly prediction oil
Gas and estimation reservoir lithology parameter.Traditional AVO analysis is exactly using Zoeppritz equation or its approximate equation by actual seismic road
A kind of inversion method of the seismologic parameter (such as density, p-and s-wave velocity) of collection record inverting estimation rock.Conventional AVO analysis method
Usually nonlinear prestack inversion problem linearization, the stability of solution is affected by initial model, and is easily trapped into
Local minimum, and AVO analyzes the poor prediction for being unfavorable for reservoir fluid of the obtained result resolution ratio of inversion method.
Summary of the invention
Aiming at the problems existing in the prior art, it is an object of the invention to solve in deficiencies of the prior art
At least one of.For example, it is an object of the invention to solve the problems, such as that traditional AVO analysis resolution ratio is lower, precision is not high.
To achieve the goals above, the present invention provides a kind of based on the indication using prestack seismic amplitude of geostatistical analysis with offset distance
Change oil gas forecasting method.The oil gas forecasting method includes: A, establishes oil and gas indication curve according to log data, in the oil
On gas indicative curve, oil gas section has the first oil and gas indication value, and non-oil gas section has the second oil and gas indication value；B, it is calculated
AVO attribute volume；C, analysis obtains the oil and gas indication curve optimal AVO category best with well bypass road AVO attribute data correlation
Property data volume；D, by oil gas section part non-in oil and gas indication curve and oil gas section part respectively with the optimal AVO attribute data
Body carries out histogram analysis, and the subordinating degree function of non-oil gas section part and oil gas section part in oil and gas indication curve is calculated and closes
System；E, geostatistical analysis is carried out to oil and gas indication curve and obtains variogram；F, using the subordinating degree function relationship and
The variogram carries out oil gas sunykatuib analysis, obtains petroleum-gas prediction result.In an exemplary embodiment of the present invention, institute
State amplitude variation with Offset attribute volume include L1 (norm), L2 (two norms), P+G, P-G, P*G, L1P+G, L1P-G,
L1P*G, L2P+G, L2P-G, L2P*G, wherein P represents intercept, and G represents gradient.
In an exemplary embodiment of the present invention, the step F may include: F01, in amplitude variation with Offset
Data grids are created on attribute volume；Grid node on F02, lookup data grids, and judge whether grid node needs to simulate,
Wherein, needing grid node to be simulated is the unknown grid node of uncertain oil and gas indication value, does not need the grid simulated
Node is the known grid node for having determined that oil and gas indication value；F03, lookup need in unknown grid node field to be simulated
Grid node is known, until known grid node reaches predetermined quantity；F04, pass through Kriging regression algorithm, utilize the predetermined number
The known grid node of amount calculate unknown grid node gram in gold number, then using gram in gold number and the variogram calculate
Golden probability value in obtaining gram；F05, using unknown grid node gram in golden probability value and corresponding amplitude variation with Offset category
The value of property data volume, Combined Ration determines the oil and gas indication value of unknown grid node to the subordinating degree function relationship, and will determine
The unknown grid node of oil and gas indication value is as known grid node；F06, step F02 to F05 is repeated, until determining institute
The oil and gas indication value for the unknown grid node having.
In an exemplary embodiment of the present invention, it in the step F02, can sequentially be swum according to random walk
It walks data grids and searches grid node；
In an exemplary embodiment of the present invention, it in the step F03, can be carried out in a manner of spiral search
It searches.
In an exemplary embodiment of the present invention, in the step F04, using gram in Kriging regression algorithm
In golden weight coefficient in golden equation calculation gram, calculate unknown grid node gram in golden probability value.
Compared with prior art, the beneficial effect comprise that improving the precision and resolution ratio of fluid prediction.
Detailed description of the invention
Fig. 1 shows the petroleum-gas prediction side prestack AVO based on geostatistics of an exemplary embodiment of the present invention
The flow chart of method oil gas simulation steps.
Fig. 2 shows the petroleum-gas prediction sides prestack AVO based on geostatistics of an exemplary embodiment of the present invention
The flow chart of method point simulation.
Specific embodiment
Hereinafter, the folding based on geostatistics that the present invention will be described in detail will be carried out in conjunction with exemplary embodiment and attached drawing
Preceding AVO oil gas forecasting method.
Prestack AVO oil gas forecasting method according to an exemplary embodiment of the present invention based on geostatistics may include as
Lower step:
A, oil and gas indication curve is established according to log data, on the oil and gas indication curve, oil gas section has the first oil
Gas indicated value (such as 1), non-oil gas section have the second oil and gas indication value (such as 0).
B, AVO attribute volume is calculated.AVO attribute volume include L1 (norm), L2 (two norms), P+G (cut
Away from adding gradient), P-G (intercept subtracts gradient), P*G (intercept boarding degree), L1P+G, L1P-G, L1P*G, L2P+G, L2P-G, L2P*G
Equal attribute volumes.Wherein, P represents intercept, and G represents gradient.
C, analysis obtains the oil and gas indication curve optimal AVO attribute data best with well bypass road AVO attribute data correlation
Body.
D, by oil gas section part non-in oil and gas indication curve and oil gas section part respectively with the optimal AVO attribute volume
Histogram analysis is carried out, the subordinating degree function of non-oil gas section part and oil gas section part in oil and gas indication curve is calculated and closes
System.
E, geostatistical analysis is carried out to oil and gas indication curve and obtains variogram.
F, oil gas sunykatuib analysis is carried out using the subordinating degree function relationship and the variogram, obtains petroleum-gas prediction knot
Fruit.The step F is specifically included:
F01, data grids are created on amplitude variation with Offset attribute volume.
F02, according to random walk, sequentially migration data grids search grid node, and judge whether grid node needs
Simulation, wherein needing grid node to be simulated be the unknown grid node for not knowing oil and gas indication value, does not need to be simulated
Grid node is the known grid node for having determined that oil and gas indication value.
F03, the known grid node needed in unknown grid node field to be simulated is searched in a manner of spiral search, directly
Reach predetermined quantity to known grid node.
F04, pass through Kriging regression algorithm, the known grid node of the predetermined quantity is utilized to calculate unknown grid node
Gram in gold number, then using gram in gold number and the variogram be calculated gram in golden probability value.
F05, using unknown grid node gram in golden probability value and corresponding amplitude variation with Offset attribute volume
Value, Combined Ration determines the oil and gas indication value of unknown grid node to the subordinating degree function relationship, and will be determined that oil gas refers to
The unknown grid node of indicating value is as known grid node.
F06, step F02 to F05 is repeated, until determining the oil and gas indication value of all unknown grid nodes.
Major technique thinking of the invention is the attribute volume for calculating AVO, by series of computation, is converted to 0 and 1 composition
Data volume, 1 Indication of Oil-Gas, the 0 non-oil gas of instruction realizes oil and gas detection.In an exemplary embodiment of the present invention, it is based on
The prestack AVO oil gas forecasting method of geostatistics may include steps of:
(1) a HCI indicative curve is established, HCI curve is an oil gas section HCI value by well logging data analysis first
The indicated value curve for being 0 for 1, non-oil gas segment value.The indicated value of however, the present invention is not limited thereto, oil gas section and non-oil gas can be it
It is any both can to distinguish different values.Here, HCI is the abbreviation of Hydrocarbon Indicator, and HCI curve is exactly
Oil and gas indication curve, accuracy are controlled by log, and HCI is the curve of an Indication of Oil-Gas and water being made of 0 and 1.
(2) by calculating that tradition AVO analyzes as a result, obtain a series of relevant AVO attribute volumes, for example, L1, L2, P+G,
The attribute volumes such as P-G, P*G, L1P+G, L1P-G, L1P*G, L2P+G, L2P-G and L2P*G, wherein P is intercept, and G is gradient, L1
For a norm, L2 is two norms.
(3) correlation between analysis HCI curve and AVO attribute track data by well, analyzes and obtains HCI-AVO attribute phase
The highest HCI-AVO attribute curve of closing property, and it is saved.
(4) histogram analysis is carried out to HCI-0 and HCI-1 curve to the HCI-AVO attribute curve of preservation, and be calculated
The subordinating degree function relationship of HCI-0 and HCI-1.Here, HCI-AVO attribute curve is by HCI curve and well bypass road AVO attribute
The best AVO attribute of data dependence, and by its AVO attribute data corresponding to 0 and 1 save respectively to HCI-0 and HCI-1
In, so that followed by using, specifically, obtained subordinating degree function is the 4. step use in (6) step.HCI-0 is
Refer to non-oil gas section part in oil and gas indication curve, oil gas section part in HCI-1 oil and gas indication curve.
(5) geostatistical analysis is carried out to the HCI indicative curve that front inputs and obtains variogram, for HC simulation point
It is used in analysis method.Specifically, variogram the 3. using in step in (6) step)
(6) HC simulation is carried out, process is as shown in Figure 1 and Figure 2, it is realized by following steps:
1. according to random walk sequentially migration by not no data value grid node.Sequentially migration is random walk
Refer to that herein is in sequentially search grid node in the random walk of foundation by certain sequential search grid node.
2. the known node (i.e. known grid node) in neighborhood is searched in a manner of spiral search at the grid node.
Known node has value, and practical is exactly the point on log, has had built up grid node here, and belonging to well logging
The indicated value of the HCI in well logging is imparted on the point of position.
3. by ordinary kriging interpolation algorithm gram in golden weight coefficient in golden equation calculation gram, calculate the point (i.e.
Unknown mesh point) indicated value probability value P*；I.e. the value of unknown point is sought by ordinary kriging interpolation method.
4. using the value of AVO attribute volume corresponding to the indicator Kriging probability value P* and the grid node sought,
Combined Ration to degree of membership relational matrix, two o'clock (gold probability value P* and AVO attribute value in gram) determine HC (oil gas) indicated value (0 or
1) indicated value that, then this is calculated is added to known point.As soon as a unknown point has been calculated, the value of unknown point is obtained, so
After add it to known points according in, become the known data point that can be used in subsequent cycle.
5. repeat step 1. -4., until calculate the indicated values of all unknown points, EP (end of program).
The model of random distribution is randomly generated using geostatistical analysis process by the present invention, and using solution global optimum
The method of change problem can effectively solve the problems, such as that the nonuniqueness in inverting and tradition AVO inverting are affected by initial model
The problem of, it is more preferable compared to traditional AVO inversion method effect, and the resolution ratio of reservoir fluid prediction can be greatly improved, it improves
To the accuracy rate of thin-layer fluid identification.
Although having been combined attached drawing above and exemplary embodiment describing the present invention, those of ordinary skill in the art
It will be apparent to the skilled artisan that can be carry out various modifications to above-described embodiment in the case where not departing from spirit and scope of the claims.
Claims (5)
1. a kind of change oil gas forecasting method with offset distance based on the indication using prestack seismic amplitude of geostatistics, which is characterized in that the oil
Gas prediction technique the following steps are included:
A, oil and gas indication curve is established according to log data, on the oil and gas indication curve, there is oil gas section the first oil gas to refer to
Indicating value, non-oil gas section have the second oil and gas indication value；
B, amplitude variation with Offset attribute volume is calculated；
C, analysis obtains the optimal vibration best with well bypass road amplitude variation with Offset attribute data correlation of oil and gas indication curve
Width is with offset distance change to attributes data volume；
D, oil gas section part non-in oil and gas indication curve and oil gas section part are changed with the optimal amplitude with offset distance respectively
Attribute volume carries out histogram analysis, and being subordinate to for non-oil gas section part and oil gas section part in oil and gas indication curve is calculated
Spend functional relation；
E, geostatistical analysis is carried out to oil and gas indication curve and obtains variogram；
F, carry out oil gas sunykatuib analysis using the subordinating degree function relationship and the variogram, obtain petroleum-gas prediction as a result,
Wherein, the step F includes:
F01, data grids are created on amplitude variation with Offset attribute volume；
Grid node on F02, lookup data grids, and judge whether grid node needs to simulate, wherein need net to be simulated
Lattice node is the unknown grid node of uncertain oil and gas indication value, and not needing the grid node simulated is to have determined that oil gas refers to
The known grid node of indicating value；
F03, the known grid node needed in unknown grid node field to be simulated is searched, until known grid node reaches pre-
Fixed number amount；
F04, pass through Kriging regression algorithm, gram of unknown grid node is calculated using the known grid node of the predetermined quantity
In gold number, then using gram in gold number and the variogram be calculated gram in golden probability value；
F05, using unknown grid node gram in golden probability value and corresponding amplitude variation with Offset attribute volume value,
Combined Ration determines the oil and gas indication value of unknown grid node to the subordinating degree function relationship, and oil and gas indication value will be determined
Unknown grid node as known grid node；
F06, step F02 to F05 is repeated, until determining the oil and gas indication value of all unknown grid nodes.
2. according to claim 1 change oil gas forecasting method with offset distance based on the indication using prestack seismic amplitude of geostatistics,
Be characterized in that, the amplitude variation with Offset attribute volume include L1, L2, P+G, P-G, P*G, L1P+G, L1P-G, L1P*G,
L2P+G, L2P-G and L2P*G, wherein P is intercept, and G is gradient, and L1 is a norm, and L2 is two norms.
3. according to claim 1 change oil gas forecasting method with offset distance based on the indication using prestack seismic amplitude of geostatistics,
It is characterized in that, in the step F02, according to random walk, sequentially migration data grids search grid node.
4. according to claim 1 change oil gas forecasting method with offset distance based on the indication using prestack seismic amplitude of geostatistics,
It is characterized in that, in the step F03, is searched in a manner of spiral search.
5. according to claim 1 change oil gas forecasting method with offset distance based on the indication using prestack seismic amplitude of geostatistics,
Be characterized in that, in the step F04, using in Kriging regression algorithm gram in golden weight coefficient in golden equation calculation gram,
Calculate unknown grid node gram in golden probability value.
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